Pump devices are commonly used to deliver one or more fluids to a targeted individual. For example, a medical infusion pump device may be used to deliver a medicine to a patient as part of a medical treatment. The medicine that is delivered by the infusion pump device can depend on the condition of the patient and the desired treatment plan. For example, infusion pump devices have been used to deliver insulin to the vasculature of diabetes patients so as to regulate blood glucose levels.
Some embodiments of a medical infusion pump system can include a continuous glucose monitoring device for providing feedback data (e.g., blood glucose levels) to the infusion pump. The infusion pump, in turn, can process the data using its controller, which may take or suggest actions in response to the data. For example, the infusion pump's controller can provide an alarm if the blood glucose level is above or below a generally safe range.
In some embodiments, an insulin pump's controller may also provide an alarm if the controller predicts the patient's future blood glucose level will go above or below a threshold level. But, the ability of a pump's control algorithms to make an accurate prediction of the patient's future blood glucose level can be adversely affected by certain factors. For example, in some circumstances, the dosage of medicine delivered by the infusion pump acts within the patient's body over a long period of time. Such conditions, for example, may cause a patient to have an amount of non-activated insulin in his or her system even hours after the insulin dosage was dispensed from the infusion pump device. If this non-activated insulin is not taken into account by the pump's controller when predicting the patient's future blood glucose levels, the accuracy of the prediction will be adversely affected. Similarly, it may take hours for food that was consumed by a patient to impart its full effect on the patient's blood glucose levels. In some circumstances, this factor can affect the accuracy of the blood glucose prediction.